Automatically inferring data relationships of datasets
US11061935B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 1, 2019 |
| Grant date | Jul 13, 2021 |
| Priority date | — |
| Expiry date | Sep 27, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described herein is a system and method for inferring data relationships of a plurality of datasets. Data contents (and optionally metadata) of the plurality of datasets are scanned to extract features of each of the datasets. Features can be related to a structure of data, a profile of data within the dataset, and/or metadata of the dataset. Each feature has an associated weight. The datasets can be clustered into clusters based on at least some of the weighted features (e.g., based on a sim-hash or min-hash of the dataset). A precise similarity metric is computed between datasets in each cluster based on their weighted features. Datasets with precise similarity metrics above a threshold quantity are inferred to be being likely related. Information is provided regarding the inferred likely related datasets.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.